The evolution of data

Digitalisation is rapidly advancing our understanding of sustainability from an investment perspective. Twenty years ago, when we first started assessing the sustainability of companies’ business practices, our ability to find high-quality, verifiable data was more limited than it is today. But, as the world of non-financial data relating to companies and countries has expanded, our ability to analyse and understand it has grown exponentially.

 

 

 

Today, we work in partnership with a number of carefully selected data providers to ensure our understanding of corporate sustainability is based on as full an information set as possible. Over the last two decades, we have diversified and deepened our extra-financial dataset, building in forward-looking metrics, for example, which we believe gives us a much better understanding of sustainability. This is a critical step in making sure our data and analysis is truly investment relevant so we can construct portfolios that are well positioned to capture opportunities and mitigate risks associated with the transition to a more sustainable economic model.

 

What the data actually says

In our opinion, for a company to deliver long-term value, it needs to be focused on its broad business ecosystem of stakeholders consisting of regulators, shareholders, employees, clients, suppliers, the environment, and its local community. We believe that business practices drive financial performance in the same way that revenues or costs would. Our analysis therefore needs to ascertain how a company is working to build a more balanced ecosystem.

Although the conventional data sources we use are globally of good quality, they have some inherent weaknesses that we try to address by alternative means. For example, most of the conventional ESG data are provided by companies themselves through questionnaires or ESG reports, and are collected by specialized data providers. This naturally favours larger companies with the resources to spend more on creating transparency around their social and environmental practices.

While ESG scoring is a useful guide in terms of which companies have more sustainable practices than others, it does not reveal who is making real, measurable progress over time.

To really understand which companies are committed to more sustainable business practices, we need more data than external third-party ESG ratings would give us, and we need to be able to dig deeper into what that data is actually telling us.

 

Decision-useful data: Avoiding the ‘greenwashers’

This is why we believe diverse, high-quality raw data is paramount when it comes to integrating sustainability into portfolios.

By focusing on the raw data, our analysts can challenge, verify and enhance the information by diversifying sources and exchanging views with management teams. Engaging directly with corporates is particularly important for emerging market companies and for small-cap stocks, where data coverage can be insufficient. We have also developed our own ESG questionnaires to gather information from companies that are not yet covered by traditional data providers.

Our team then cleans and standardises all of this non-financial information into a common calculation platform, which stores all historical data. This allows us full transparency into the data and, as a consequence, the flexibility to adjust for biases, and build and test different strategies.

For example, to overcome the size-bias inherent in many ESG ratings, we reconstruct our own rating using a proprietary methodology. Our scoring construction aims to measure how companies are aligned with best practices in term of ESG, how they manage the most material ESG risks related to their activities, and whether they are sincere about adopting good practices. Our specialized ESG team emphasize indicators that reflect concrete, tangible and measurable results achieved by companies and tend to avoid biases induced by good communication and “green marketing”.

This methodology, which is our ‘CAR’ approach, breaks down the data into ‘Consciousness’, ‘Action’ and ‘Results’. Over the lifecycle of a company, we would expect to see companies transition from Consciousness, through Action, to Results.

 

 

This allows us to better differentiate between the talkers, the do-ers and the real achievers to give the portfolio management teams a much deeper understanding of genuine corporate sustainability. A company may achieve a high ESG score, but be less sustainable than another company with a lower ESG score that is delivering genuine, measurable results.

By applying our own methodology to the raw data, we can better identify companies that are actually becoming more sustainable, and those who are just talking about it. The latter is a sign they might be ‘green washing’.

 

Integration, informed engagement and bespoke portfolios

All our portfolio management and research teams can then use this non-financial information alongside their financial analysis to assess the investment case of the company.

Our portfolio managers also use this data set to inform their dialogue and engagement with companies, both to improve portfolio outcomes, but also to encourage companies to transition towards more sustainable business practices.

This provides a highly useful feedback loop to improve our data and understanding of the sustainability of company’s business practices. Our portfolio managers are able to use their regular interactions with companies to modify and update our ESG scoring based on their qualitative judgement. As a result, our portfolio management teams are better able to form an opinion on risks and opportunities associated with the way a company behaves.

A diverse set of raw data also gives us a greater ability to adapt our approach to suit the individual requirements and objectives of our clients. Increasingly, we see demand to mitigate risks associated with climate change, for example, or to capture the opportunities the transition to a low-carbon economy will inevitably create.

‘Alternative’ and ‘Big’ Data

Climate change is arguably the most urgent of the sustainability challenges investors are grappling with today as both the physical effects of climate change, and transition risks associated with meeting the goals of the Paris Agreement take their toll on investment portfolios.

Climate change is also an area where the availability of data is rapidly improving, but so is the complexity of the issue, which calls for new approaches to data gathering and analysis.

We have developed a methodology for calculating the impact a business has in terms of carbon emissions and water consumption. We can favour companies that are both more resilient to transition, and creating a positive impact on society and the environment.

However, embedding climate risk and opportunity into portfolios requires a broader perspective to understand how these dynamics affect the expected risk and returns a company presents over the long-term. How resilient are global corporations or global supply chains to the changing ecological effect of a warming planet, for example, or to the varying regulatory regimes being introduced to limit further warming to 2° Centigrade this century?

Understanding how resilient companies are has become a critical piece of investment-relevant information, particularly as pressure mounts on asset owners and managers to report in line with disclosure initiatives like the Taskforce for Climate Related Financial Disclosure.

Big Data has a lot to offer in terms of its ability to capture the systemic, multi-layered nature of these risks and opportunities. In turn, this means we have a much more informed information set.

Alternative and Big Data also have a lot to offer in terms of verification of our raw data and can, in our opinion, meaningfully enhance our understanding, particularly around social issues, where the data can still be harder to find. This is a key pillar of our evolution at Lombard Odier Investment Managers.

As the availability of data improves, we need to continually adapt and innovate our approach to collecting, verifying, and analysing data so that we can ensure our portfolio managers have as much investment-relevant information as possible. In turn, this helps to ensure our portfolios are built on a robust, forward-looking understanding of corporate sustainability.